Candidate intelligence — not candidate data.
A LinkedIn profile is data. An evidence dossier is intelligence. Majhi OS builds structured, scored, risk-flagged candidate briefs before any outreach is unlocked — so every candidate who reaches the hiring manager has already cleared the quality gate.
The Problem With Data
Most recruiting delivers candidates. Majhi OS delivers intelligence.
The standard recruiting output is a list of profiles. LinkedIn URL, current title, years of experience. The hiring manager has to do the intelligence work themselves — assessing fit, spotting risk, estimating compensation, calibrating cultural alignment.
Majhi OS inverts this. By the time a candidate reaches the hiring manager, the intelligence work is done. The evidence dossier answers the questions before they're asked.
Fit Score
A composite score across role criteria: industry background match, title trajectory, company stage alignment, tenure patterns, and skill overlap. Calibrated against the mandate brief, not a generic rubric.
Risk Flags
Short tenures, counter-offer history, geographic constraints, compensation misalignment, or cultural friction signals — identified before outreach begins, not after an offer is declined.
Proof Points
Concrete evidence of relevant achievement: specific outcomes from comparable roles, relevant company stages navigated, leadership team builds completed. Not claims — evidence.
The Evidence Dossier
What every candidate dossier contains.
Every candidate who clears the QMS gate arrives with a complete structured dossier. The hiring manager reads one document — not a pile of profiles.
Role Fit Analysis
Structured comparison of candidate background against mandate criteria. Where they match, where they stretch, where they're weak. The hiring manager sees the assessment, not just the CV.
Compensation Estimate
Market-calibrated total compensation estimate based on role level, company stage, geography, and current compensation signals. Prevents offer-stage surprises on both sides.
Cultural Fit Indicators
Leadership style signals from public content, reference patterns, and company context. Not a personality test — observable, verifiable indicators that the hiring manager can probe in interview.
Availability Signal
Estimated move-probability based on tenure, company signals, and role trajectory. Prioritises outreach toward candidates most likely to engage — reducing wasted cycles on unlikely movers.
Reference Map
Network paths to credible references — people who have worked directly with the candidate in comparable roles. Referenced before offer, not after acceptance.
Mandate Fit Confidence
The system's overall confidence that this candidate is right for this mandate. Low confidence triggers human review. High confidence advances to outreach automatically.
The Outcome
82% shortlist approval. Here's why.
When we started, shortlist approval rates across most searches we reviewed were running at 38%. Hiring managers were rejecting more than half the candidates presented.
The cause: candidates arrived without intelligence. The hiring manager had to reject based on obvious gaps that should have been caught earlier. Majhi OS moved the intelligence work upstream. Approval rates followed.
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